Literature Index

Displaying 741 - 750 of 3326
  • Author(s):
    Tarpey, T., Acuna, C., Cobb, G., & De Veaux, R.
    Year:
    2002
    Abstract:
    Curriculum guidelines for a bachelor of arts degree in statistical science are proposed. These guidelines are intended for liberal arts colleges, and other institutions where statistics is taught in departments of mathematics. A flexible curriculum is described consisting of three main parts: mathematics, core statistical topics and a substantive area of study. The curriculum guidelines permit and actively encourage the rethinking of traditional courses and the development of new courses. Guidelines for a minor in statistical science are also proposed. The guidelines are the result of an Undergraduate Statistics Education Initiative workshop held in Alexandria, Virginia in April 2000.
  • Author(s):
    Rex, G., Gould, R., Notz, W. I., & Peck, R. L.
    Year:
    2001
    Abstract:
    This article is the culmination of the work on curriculum for Bachelor of Science degrees in statistical science from both the workshop on undergraduate curriculum held on April 28-29, 2000, and the symposium on improving the workforce of the future.
  • Author(s):
    JARED KEELEY,<br>RYAN ZAYAC,<br>CHRISTOPHER CORREIA
    Year:
    2008
    Abstract:
    This study examined the possibility of a curvilinear relationship between statistics anxiety and performance in a statistics course. Eighty-three undergraduate students enrolled in an introductory course completed measures of statistics anxiety and need for achievement at seven points during the semester in conjunction with six tests. Statistics anxiety scores were reliable internally and across time. Statistics anxiety decreased during the term yet paradoxically became more strongly related to performance. Curvilinear models were better predictors of test performance than linear, suggesting a mid-range optimal level of statistics anxiety. However, students' need for achievement proved not to mediate the relationship between anxiety and performance. The authors suggest ways these findings may influence future research in statistics anxiety and classroom management of anxiety.
  • Author(s):
    Owen P. Hall, Jr., and Ken Ko
    Year:
    2008
    Abstract:
    Globalization is bringing about a radical "rethink" regarding the delivery of graduate management education. Today, many students entering a residential MBA program do not possess an undergraduate degree in business. As a result, many business schools are increasingly turning to the Internet to provide "customized" instructional content to ensure that students can remain competitive throughout the program. The purpose of this paper is threefold: 1) to estimate student performance in a residential MBA program; 2) to outline a process for identifying specific learning support resources based on student backgrounds and capabilities; and 3) to illustrate the screening process in providing business statistics support content to students requiring additional preparation. The results show that neural net based classification techniques can effectively identify students for the purpose of providing additional learning resources. Business statistics is one area in which this screening process has been used to deliver specialized content to students with a variety of backgrounds enrolled in a MBA residential program.
  • Author(s):
    Velleman, P. F., Hoaglin, D. C.
    Editors:
    Hoaglin, D. C., Moore, D. S.
    Year:
    1992
    Abstract:
    As the link between statistics and diverse fields of application, data analysis confronts the challenge of turning data into useful knowledge.
  • Author(s):
    Burrill, G.
    Editors:
    Hirsch, C. R.
    Year:
    1992
    Abstract:
    The purpose of this volume, and others in the Addenda Series, is to provide instructional ideas and materials that will support implementation of the Curriculum and Evaluation Standards in local settings.
  • Author(s):
    Batanero, M. C., Godino, J. D., &amp; Vallecillos, M. A.
    Year:
    1991
    Abstract:
    In this work we want to underline the fact that the use of the statistical tool in experimental and social sciences, in general, and in the didactics of mathematics in particular is converted, in this field of knowledge, in a specific object of the study, due to the mathematical nature of the concepts and to the didactic processes implied.
  • Author(s):
    Konold, C., &amp; Pollatsek, A.
    Year:
    2002
    Abstract:
    The idea of data as a mixture of signal and noise is perhaps the most fundamental concept in statistics. Research suggests, however, that current instruction is not helping students to develop this idea, and that though many students know, for example, how to compute means or medians, they do not know how to apply or interpret them. Part of the problem may be that the interpretations we often use to introduce data summaries, including viewing averages as typical scores or fair shares, provide a poor conceptual basis for using them to represent the entire group for purposes such as comparing one group to another. To explore the challenges of learning to think about data as signal and noise, the authors examine the "signal/noise" metaphor in the context of three different statistical processes: repeated measures, measuring individuals, and dichotomous events. On the basis of this analysis, several recommendations are made about research and instruction.
  • Author(s):
    Teague, D. J.
    Editors:
    Vere-Jones, D., Carlyle, S., &amp; Dawkins, B. P.
    Year:
    1991
    Abstract:
    Data analysis can play an important role in bridging the gap between the world of mathematics and the student's world experience. Students study functions in class, but seldom have the opportunity to see these functions and their interactions exhibited in the world around them. As the students study the behavior of functions in calculus and precalculus courses, they learn how things should happen in theory. Through data analysis, the theory can be motivated and realised in the actual. The principles of curve fitting, re-expression, and residual analysis, offer a very exciting and enlightening basis for the motivation and derivation of many of the functions and functional concepts taught in high school algebra and in calculus. The Mathematics Department at the North Carolina School of Science and Mathematics has created, tested, and published an innovative data-driven precalculus text and is presently writing a calculus course involving many laboratory experiences from which the examples in this article are taken.
  • Author(s):
    Scheaffer, R. L.
    Year:
    2002
    Abstract:
    Provides an overview of the structure of data analysis, the interrelationship between data analysis and probability, and the connection between data analysis and other components of the mathematics curriculum. Presents a possible order for topics being consistent with modern statistical practice and allows the topics to grow as students move through grade levels.

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The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education